TerraMosaic Daily Digest: Jan 8, 2026
Daily Summary
Today's landslide research feed highlights a diverse range of topics, from fundamental mechanisms to applied hazard assessment and early warning systems. A significant portion of the research focuses on the application of advanced technologies like deep learning, InSAR, and numerical modeling to improve landslide detection, prediction, and risk assessment. Several papers address the impact of specific triggers such as rainfall, earthquakes, and snowmelt on landslide initiation and propagation. There's also a strong emphasis on understanding the role of soil properties, vegetation, and geological structures in landslide susceptibility. Studies are increasingly incorporating multi-source data and hybrid modeling approaches to capture the complex interactions between various factors contributing to landslide hazards. A growing number of papers focus on the cascading effects of landslides, including debris flows, damming, and even tsunamis, emphasizing the need for integrated risk management strategies. The geographical scope is global, with studies spanning from the Himalayas and the Andes to China, Europe, and North America, reflecting the widespread nature of landslide hazards. The integration of physical models with data-driven approaches is a prominent trend, aiming to improve the accuracy and reliability of landslide predictions.
Key Trends
- Deep Learning & Machine Learning: Numerous papers leverage deep learning (CNN, LSTM, GNN) and machine learning techniques for landslide susceptibility mapping, displacement prediction, and rockfall detection.
- InSAR Technology: Several studies utilize InSAR (Interferometric Synthetic Aperture Radar) for monitoring ground deformation, assessing landslide vulnerability, and mapping land subsidence.
- Numerical Modeling: A significant number of papers employ numerical modeling techniques (MPM, SPH, DEM, FEM) to simulate landslide dynamics, rainfall infiltration, and slope stability.
- Debris Flows: A recurring theme is the study of debris flows, including their initiation mechanisms, propagation dynamics, and impacts on infrastructure and archaeological sites.
- Rainfall-Induced Landslides: Many studies focus on understanding the role of rainfall in triggering landslides, with investigations into rainfall thresholds, infiltration processes, and soil moisture dynamics.
- Earthquake-Triggered Landslides: Several papers address the assessment of landslide susceptibility and the modeling of landslide dynamics in earthquake-prone regions.
Selected Papers
This digest features 143 selected papers from 1,489 papers analyzed across multiple journals. Each paper has been evaluated for its relevance to landslide research and includes links to the original publications.
1. What controls the distribution of post-Little Ice Age landslides around the South Patagonian Icefield?
Core Problem: Understanding landslide distribution in deglaciated mountain regions for geohazard risk assessment.
Key Innovation: Orogen-scale assessment of landslide density using high-resolution satellite imagery and statistical evaluation of environmental variables.
2. Testing NDVI and U-Net for automated mapping of multiple-occurrence regional landslide events using satellite and aerial multispectral data (Casola Valsenio, Emilia-Romagna, Northern Apennines, Italy)
Core Problem: Automated landslide mapping after a severe multiple occurrence regional landslide event.
Key Innovation: Comparison of NDVI change and U-Net methods applied to satellite and aerial multispectral data for rapid landslide mapping.
3. Limited equilibrium and finite element modeling of critical groundwater conditions driving the Achoma landslide, Central Andes REgion, Arequipa, Peru
Core Problem: Identifying triggers for a rotational landslide in the Colca Valley to inform future management strategies.
Key Innovation: Computer modeling of slope stability to test groundwater and infiltration scenarios, linking rainfall, irrigation, and water conveyance leakage to landslide triggering.
4. Quantitative analysis of pore-water pressure behaviors in a rapid and long-runout landslide based on ring shear test
Core Problem: Examining the hypermobility mechanisms of a rainfall-induced rapid and long-runout landslide.
Key Innovation: Undrained loading and high-speed ring shear tests to quantify pore-water pressure generation and its role in landslide mobility.
5. Prediction of enhanced creep landslide displacement by analyzing multi-time-scale displacement impact factors using convolutional neural network (CNN)
Core Problem: Prediction of landslide displacements during creep stages for hazard and risk management.
Key Innovation: Hybrid modeling framework incorporating multi-time-scale components of rainfall and reservoir water level into a CNN-LSTM model for improved landslide displacement prediction.
6. EENet: An edge-enhanced network for robust rockfall detection in complex mountainous environments
Core Problem: Accurate and timely detection of rockfalls in mountainous transportation corridors.
Key Innovation: Lightweight Edge-Enhanced Network (EENet) with an Edge Spatial Stem and Global Edge Fusion Network for robust rockfall detection under complex environmental conditions.
7. The interaction of gas hydrate with submarine landslides studied with cascading machine learning
Core Problem: Quantifying the impact of gas hydrates on submarine landslide susceptibility.
Key Innovation: Cascaded machine learning framework integrating geological parameters with Potential Hydrate Occurrence Depth for landslide susceptibility assessment.
8. 3D MPM simulation of the coseismic Daguangbao landslide with a state-dependent frictional weakening model
Core Problem: Reproducing the dynamic failure and runout process of the Daguangbao landslide triggered by the Wenchuan earthquake.
Key Innovation: MPM framework with a state-dependent frictional weakening contact law and a strain-softening Mohr–Coulomb model for simulating coseismic landslide dynamics in 3D.
9. Database development and geometric characterization of the shallow landslides triggered bythe 16 June 2024 extreme rainfall event in Meizhou, Guangdong (China)
Core Problem: Analyzing widespread shallow landslides triggered by an extreme rainstorm to enhance regional landslide early warning capabilities.
Key Innovation: Detailed landslide catalog database constructed using high-resolution remote sensing imagery and quantitative analysis of landslide geometric properties.
10. Multi-pulse seismic effect in regional scale landslide using an improved smoothed particle hydrodynamics method
Core Problem: Simulating earthquake-induced landslide hazards across square-kilometer-scale terrains under multi-pulse ground motions.
Key Innovation: Improved GPU-accelerated smoothed particle hydrodynamics model with a novel dynamic boundary condition to resolve seismic wave interactions with inclined surfaces.
11. Study of the strength degradation of the saturation loess using ring shear tests
Core Problem: Studying the mechanisms of strength degradation of loess during water infiltration to understand loess landslide behavior.
Key Innovation: Stress-controlled and velocity-controlled ring shear tests to reveal the strength degradation and liquefaction mechanisms of saturated loess.
12. Integrated time-lapse ERT and airborne laser scanning–photogrammetry DEM analysis of a reservoir-induced landslide in central Poland
Core Problem: Quantifying the landslide reactivation mechanism at a reservoir shoreline and identifying hydrological thresholds for early warning.
Key Innovation: Integration of time-lapse electrical resistivity tomography (TL-ERT) with archival airborne datasets to resolve the drivers and timing of reservoir-controlled reactivation.
13. Feature Selection and Comparison of Logistic Regression and Random Forest for Stability Assessment of Landslide Dams
Core Problem: Reliable stability assessment of landslide dams (LDs) with limited and heterogeneous data.
Key Innovation: Machine learning framework integrating physically meaningful composite features with ensemble and statistical modeling for interpretable and data-driven LD stability assessment.
14. Unravelling slow kinematics of deep-seated gravitational slope deformations (DSGSDs) in the Himalaya: a case study of the Shiala Landslide Complex, Southeastern Kumaun Himalaya, India
Core Problem: Investigating climate-tectonic and hydro-lithological controls on deep-seated gravitational slope deformations (DSGSDs) in the Himalayas.
Key Innovation: Interdisciplinary approach combining geological mapping, PS-InSAR, geotechnical analysis, and runout modeling to understand the mechanism of a DSGSD system.
15. Experimental study on the initiation mechanism of debris flow dry heads
Core Problem: Uncovering the mechanisms governing the formation and maintenance of dry heads in debris flows.
Key Innovation: Laboratorial experiments using a custom flume and high-speed photography to trace pebble dynamics and analyze the two-phase debris flow structure.
16. A multi-method framework for hazard assessment of high-altitude landslides: a case study of the Luodexi Landslide on the Eastern Tibetan Plateau
Core Problem: Addressing the challenges in identification and risk assessment of high-altitude landslides.
Key Innovation: Deformation analysis method coupling ground surface temperature with InSAR-measured deformation characteristics and a multi-method assessment framework for hazard assessment.
17. Formation mechanism and failure modes of loess-mudstone landslides in fault-active regions of the southern loess plateau of China
Core Problem: Elucidating the failure mode of loess-mudstone landslides (LMLs) under the action of a geological environment shaped by fault activity.
Key Innovation: Physical model tests considering various slope structures, topographic features, lithology composition, erosion morphologies, and rainfall intensities to analyze the stability and failure mechanisms of LMLs.
18. Correlation of geomorphological features, geomechanical properties, and clustering of passive seismic recordings for translational rock block slide zoning
Core Problem: Characterizing rock block slides in soft rocks using passive seismic data.
Key Innovation: Correlation of passive seismic data with rock block geomechanical properties and geomorphological features for landslide zoning.
19. Interplay of rheology, deformation, and land use land cover in triggering cluster landslides: evidences from May 2022 landslides in Dima Hasao, Northeast India
Core Problem: Understanding hill-slope dynamic evolution in triggering cluster landslides.
Key Innovation: Analysis of the rheological behaviour of representative samples, analogue experiments, and land use land cover changes to understand landslide triggers.
20. Characteristics and mechanism of high-vegetation-coverage recurrent debris flow disaster chain: Insights from a case in the Qinling Mountains, China on July 19, 2024
Core Problem: Understanding the spatiotemporal characteristics and recurrence mechanisms of vegetation-masked geological hazard chains.
Key Innovation: Integrated UAV-based remote sensing, multi-source geospatial data fusion, and field geomorphological mapping to decipher the recurrence mechanisms of debris flows.
21. Slope failure level prediction using a hybrid convolutional long short-term memory network based on microseismic monitoring data
Core Problem: Accurate prediction of slope failure severity levels for effective disaster prevention and mitigation.
Key Innovation: Hybrid convolutional long short-term memory (LSTM) model with attention mechanism and improved gating mechanism for slope early warning.
22. Damage quantification and response surface prediction of blasting-induced slope stability based on DFN
Core Problem: Analyzing the coupled effects of multiple blasting parameters on slope failure.
Key Innovation: Three-dimensional DFN–PFC-based slope stability analysis method integrating discrete fracture network (DFN)–based damage quantification with response surface methodology (RSM) for multi-parameter optimization.
23. Upper-bound limit analysis of near-fault jointed slopes stability based on the pulse-like ground motion and slope surface concave convex characteristics: a case study
Core Problem: Dynamic stability of near-fault jointed slopes under pulse-like ground motion and concave convex characteristics.
Key Innovation: Construction of up rotation-lower translation and up translation-lower rotation models for irregular geometric slopes with n polyline segments, incorporating concave convex characteristics and failure modes.
24. Representative profile model: a new physically-based model using slope unit for hazard assessment of colluvial landslides at large scale
Core Problem: Refined assessment of landslide hazard at large scale using a physically-based model.
Key Innovation: Physically-based model called representative profile model (RPM) that takes the slope unit as the assessment unit and couples the slope surface morphology, Quaternary deposits thickness and ground water level.
25. Optimizing graph neural networks for rockfall susceptibility mapping: a feature selection and hazard prediction approach
Core Problem: Enhancing rockfall prediction accuracy by integrating feature selection and optimization techniques with Graph Neural Networks (GNNs).
Key Innovation: Utilizing GraphSAGE for rockfall susceptibility prediction, achieving the highest F1 Score, Kappa, and Accuracy, and demonstrating the efficacy of GNNs in geohazard prediction.
26. Acceleration of the Gradenbach-Eggerberg rock slope deformation
Core Problem: Acceleration of rock slope deformation leading to potential floods and debris flows.
Key Innovation: Comprehensive analysis of multi-decadal monitoring data reveals distinct kinematic domains and identifies snowmelt as the primary trigger for acceleration events, enabling velocity forecasting for early warning.
27. Rainfall-induced landslide simulation via a coupled FVM-DEM method
Core Problem: Simulating the entire failure process of rainfall-induced landslides in granite residual soil.
Key Innovation: A coupled finite volume and discrete element (FVM-DEM) framework to simulate both unsaturated seepage and soil mechanical behaviour, capturing the spatiotemporal evolution of rainfall infiltration and its influence on soil strength degradation.
28. Physical modelling to map the rheological and morphological dynamics along with entrainment mechanics of debris flow: a comprehensive review of the state of the art
Core Problem: Understanding the dynamic morphological and rheological properties of debris flows.
Key Innovation: A consolidated overview of recent advancements in debris flow experiments, such as the effects of material and geometric parameters on flow dynamics, mechanisms of evolution of excess pore water pressure, entrainment mechanisms, and the classification of experiments based on the type and size of experimentation.
29. Investigating the coupling effect of loading rate and initial static shear stress on landslide and soil liquefaction within an energy-based framework
Core Problem: Understanding the coupled effects of loading rate and initial shear stress on soil shear behavior and their influence on strength characteristics and energy dissipation.
Key Innovation: Laboratory shear tests under varying initial shear stress levels and loading rates to quantify their coupled effects on stress–strain responses, strength parameters, and energy components.
30. Deformation trend prediction for hydraulically driven landslides in reservoir areas: modeling from high temporal resolution data
Core Problem: Predicting long-term deformation trends of deposit-layer landslides in reservoir areas under the combined influence of seasonal precipitation and periodic water-level operations.
Key Innovation: Integration of daily displacement measurements, rainfall data, and reservoir water-level observations with a deep learning-based prediction model (LSTM-SVM) to forecast landslide deformation trends.
31. Landslide susceptibility assessment through bivariate models (weight of evidence and frequency ratio) in Pesanggaran, East Java, Indonesia
Core Problem: Quantifying landslide susceptibility in the Pesanggaran District using an integrated bivariate modeling framework.
Key Innovation: Combining the Weight of Evidence (WoE) and Frequency Ratio (FR) approaches with remote sensing-GIS techniques to generate landslide susceptibility maps and identify influential factors.
32. The comparison of analytical hierarchy process, frequency ratio, and deep learning-based approaches for landslide susceptibility mapping in the Northern Chiang Mai watershed Basins, Thailand
Core Problem: Developing reliable landslide susceptibility maps for the Northern Chiang Mai Watershed Basins (NCMBs) for risk reduction and planning.
Key Innovation: Employing traditional methods (AHP and FR) alongside advanced deep learning approaches (CNN and LSTM) to identify areas prone to landslide susceptibility and determine the underlying causative factors.
33. A deep learning-based model for endorsing predictive accuracies of landslide prediction: insights into soil moisture dynamics
Core Problem: Predicting volumetric water content (VWC) to mitigate shallow, rainfall-induced landslides.
Key Innovation: A framework that integrates deep learning (DL) with the physical dynamics of the VWC subsurface behavior, enabling both point and interval predictions and demonstrating improved accuracy and a practical data-sharing mechanism.
34. Failure mechanism of a snowmelt-related loess landslide group in Ten-zan, China
Core Problem: Understanding the failure mechanism of snowmelt-related loess landslides.
Key Innovation: Investigating the failure mechanism of loess landslides triggered by snowmelt in the Ten-zan region of China.
35. Assessing soil thickness and distribution in subtropical typhoon areas: an integration of advanced geomorphological surveys and ensemble learning approaches
Core Problem: Predicting soil thickness and its spatial distribution in subtropical-typhoon regions to improve predictions of debris flows and landslides.
Key Innovation: Integrating geomorphological surveys with ensemble machine learning techniques to develop a watershed-scale map of unstable layer thickness.
36. Forecasting seismic rockfalls through a fragility–antifragility and topographic–anisotropic framework: The 2022 Ms. 6.1 Lushan earthquake
Core Problem: Forecasting seismic rockfalls.
Key Innovation: Using a fragility–antifragility and topographic–anisotropic framework to forecast seismic rockfalls.
37. Bio-geotechnical reinforcement of purple soil slopes: The synergistic effects of xanthan gum biopolymer and planting density
Core Problem: Reinforcing purple soil slopes.
Key Innovation: Using xanthan gum biopolymer and planting density to reinforce purple soil slopes.
38. Earthquake-triggered landslide susceptibility modeling based on fault geometry
Core Problem: Modeling earthquake-triggered landslide susceptibility.
Key Innovation: Modeling earthquake-triggered landslide susceptibility based on fault geometry.
39. From mineral dissolution to slope failure: wet-dry cycling driven multiscale degradation of Cenozoic red-bed mudstone, NE Tibetan Plateau
Core Problem: Understanding slope failure due to mineral dissolution.
Key Innovation: Investigating wet-dry cycling driven multiscale degradation of Cenozoic red-bed mudstone.
40. Deciphering the relationship between post-fire ground deformation and debris flow activity influenced by lithological heterogeneity: Insights from a comparative analysis in southwestern China
Core Problem: Understanding the relationship between post-fire ground deformation and debris flow activity.
Key Innovation: Analyzing the influence of lithological heterogeneity on post-fire ground deformation and debris flow activity.
41. Contribution of time-evolving landslide sources to the anomalous tsunami observed in the 2024 Noto earthquake
Core Problem: Understanding the contribution of landslides to tsunamis.
Key Innovation: Analyzing the contribution of time-evolving landslide sources to the anomalous tsunami observed in the 2024 Noto earthquake.
42. NADbP: A morphological method to characterize the coupling between landslide evolution and river profile disequilibrium
Core Problem: Characterizing the coupling between landslide evolution and river profile disequilibrium.
Key Innovation: Developing a morphological method (NADbP) to characterize the coupling between landslide evolution and river profile disequilibrium.
43. Two-phase SPH-DEM modeling of the superelevation phenomenon of debris and mud flows
Core Problem: Modeling the superelevation phenomenon of debris and mud flows.
Key Innovation: Using two-phase SPH-DEM modeling to simulate the superelevation phenomenon of debris and mud flows.
44. Deformation pattern of a creeping slope revealed by continuous GNSS monitoring in northern Taiwan
Core Problem: Understanding the deformation pattern of a creeping slope.
Key Innovation: Using continuous GNSS monitoring to reveal the deformation pattern of a creeping slope in northern Taiwan.
45. Ancient landslide on the Tibet Plateau(China): Reactivation mechanism and post-failure behavior prediction
Core Problem: Understanding the reactivation mechanism and post-failure behavior of ancient landslides.
Key Innovation: Investigating the reactivation mechanism and post-failure behavior prediction of an ancient landslide on the Tibet Plateau.
46. High-precision 3D seismic event (SE) location method for slopes incorporating complex strata and topographic effects: A case study of creeping slopes in the Hengduan Mountains, Eastern Tibet
Core Problem: Locating seismic events on slopes.
Key Innovation: Developing a high-precision 3D seismic event (SE) location method for slopes incorporating complex strata and topographic effects.
47. Probabilistic analysis of stress effects on an unsaturated soil slope stability using convolutional neural networks and Bayesian optimisation
Core Problem: Analyzing stress effects on unsaturated soil slope stability.
Key Innovation: Using convolutional neural networks and Bayesian optimisation for probabilistic analysis of stress effects on unsaturated soil slope stability.
48. Analysis of rockfall-induced retreat and influencing factors in a sandstone-marl interbedded rock wall in a low-elevation environment
Core Problem: Analyzing rockfall-induced retreat.
Key Innovation: Analyzing rockfall-induced retreat and influencing factors in a sandstone-marl interbedded rock wall in a low-elevation environment.
49. A 3D multiphase SPH framework for modelling soil-water interaction in rainfall-landslide-tsunami cascades
Core Problem: Modeling soil-water interaction in rainfall-landslide-tsunami cascades.
Key Innovation: Developing a 3D multiphase SPH framework for modelling soil-water interaction in rainfall-landslide-tsunami cascades.
50. Hydro-mechanical response of herbaceous root-reinforced soils and its implications for vegetated-slope stability
Core Problem: Understanding the hydro-mechanical response of root-reinforced soils.
Key Innovation: Investigating the hydro-mechanical response of herbaceous root-reinforced soils and its implications for vegetated-slope stability.
51. Assessment of regional damming probability caused by post-earthquake rainfall-induced cascading hazards
Core Problem: Assessing the probability of damming caused by post-earthquake rainfall-induced landslides.
Key Innovation: Assessing regional damming probability caused by post-earthquake rainfall-induced cascading hazards.
52. A cohesive zone model and coupled Eulerian-Lagrangian combined approach of landslide-induced waves modeling and its application on a slope of the Lancang River
Core Problem: Modeling landslide-induced waves.
Key Innovation: Developing a cohesive zone model and coupled Eulerian-Lagrangian combined approach of landslide-induced waves modeling.
53. A physics-based machine learning-informed model for predicting regional earthquake-induced landslides
Core Problem: Predicting regional earthquake-induced landslides.
Key Innovation: Developing a physics-based machine learning-informed model for predicting regional earthquake-induced landslides.
54. Prediction of static liquefaction landslides in loess: Integrating triaxial shear parameters into the sliding-block model
Core Problem: Predicting static liquefaction landslides in loess.
Key Innovation: Integrating triaxial shear parameters into the sliding-block model for prediction of static liquefaction landslides in loess.
55. Full-waveform CNN–transformer neural network for regional coseismic landslide susceptibility modeling: A case study of the 2022 Luding earthquake, China
Core Problem: Modeling regional coseismic landslide susceptibility.
Key Innovation: Using a full-waveform CNN–transformer neural network for regional coseismic landslide susceptibility modeling.
56. From hydro-meteorological thresholds towards an operational warning model for landslides at regional scale: A real-case application
Core Problem: Developing an operational warning model for landslides at regional scale.
Key Innovation: Moving from hydro-meteorological thresholds towards an operational warning model for landslides at regional scale.
57. Impacts of plant roots on debris-flow bed erosion in laboratory experiments
Core Problem: Understanding the impacts of plant roots on debris-flow bed erosion.
Key Innovation: Investigating the impacts of plant roots on debris-flow bed erosion in laboratory experiments.
58. Regional-scale inventory and initial analysis of liquefaction triggered by the 2025 Mw 7.7 Mandalay earthquake, Myanmar
Core Problem: Analyzing liquefaction triggered by the 2025 Mw 7.7 Mandalay earthquake.
Key Innovation: Conducting a regional-scale inventory and initial analysis of liquefaction triggered by the 2025 Mw 7.7 Mandalay earthquake, Myanmar.
59. Startup mechanism of locked segment–dominated rockslides: Insights from a physical model experiment replicating natural infiltration conditions
Core Problem: Understanding the startup mechanism of locked segment–dominated rockslides.
Key Innovation: Using a physical model experiment replicating natural infiltration conditions to understand the startup mechanism of locked segment–dominated rockslides.
60. Rockfall susceptibility mapping from topography perspective combing slope units and physical model-based negative sample strategy in the Yangtze Three Gorges
Core Problem: Mapping rockfall susceptibility.
Key Innovation: Mapping rockfall susceptibility from a topography perspective combing slope units and a physical model-based negative sample strategy.
61. High-density fold–cleavage structures as a controlling factor of landslides: A case study in the southern Oboke area of the Shikoku Mountains, Japan
Core Problem: Understanding the controlling factors of landslides.
Key Innovation: Investigating high-density fold–cleavage structures as a controlling factor of landslides.
62. Using paired Schmidt Hammer and terrestrial cosmogenic surface exposure dating to study the timing and style of rockfalls in the Rough River Basin, Kentucky: Results, constraints, and possible mechanisms
Core Problem: Studying the timing and style of rockfalls.
Key Innovation: Using paired Schmidt Hammer and terrestrial cosmogenic surface exposure dating to study the timing and style of rockfalls.
63. Mechanisms of landslides induced by extreme rainfall in folded mountains: Case study of Zhenba, July 1, 2023
Core Problem: Understanding the mechanisms of landslides induced by extreme rainfall.
Key Innovation: Investigating the mechanisms of landslides induced by extreme rainfall in folded mountains.
64. Insights into red-bed landslide movement from the perspective of geomorphic evolution: A case study in western Yunnan, China
Core Problem: Understanding the mechanisms and geomorphic evolution of red-bed landslides in western Yunnan, China.
Key Innovation: Applies geomorphic evolution to analyze red-bed landslide movement.
65. Gully erosion susceptibility assessment and SHAP interpretability analysis in sloping farmland of soil-rock dual structure area: A case study of Yimeng Mountain area, China
Core Problem: Assessing gully erosion susceptibility in sloping farmland with a soil-rock dual structure.
Key Innovation: Uses SHAP interpretability analysis to enhance gully erosion susceptibility assessment.
66. Multi-scenario analysis of debris flow propagation on the archaeological site of Villa Romana del Casale (Sicily, Italy)
Core Problem: Analyzing debris flow propagation and its impact on the Villa Romana del Casale archaeological site.
Key Innovation: Employs multi-scenario analysis to model debris flow propagation.
67. Objective versus subjective landslide risk: A case of Cache Creek Landslide in California
Core Problem: Comparing objective and subjective assessments of landslide risk at Cache Creek Landslide in California.
Key Innovation: Examines the differences between objective and subjective landslide risk perceptions.
68. Corrigendum to “Objective versus subjective landslide risk: A case of Cache Creek Landslide in California” [Int. J. Disaster Risk Reduct. 132 (2026) 105910]
Core Problem: Correcting errors in the original paper on objective versus subjective landslide risk at Cache Creek Landslide.
Key Innovation: Provides corrections to a previously published study on landslide risk assessment.
69. Towards reliable deep excavation monitoring through graph recurrent neural network-based spatio-temporal imputation
Core Problem: Reliable monitoring of deep excavations is crucial for preventing landslides and ensuring the safety of nearby structures.
Key Innovation: Using graph recurrent neural networks for spatio-temporal imputation to improve the reliability of deep excavation monitoring.
70. An advanced data reliability assessment method with application to high rockfill dam deformation analysis
Core Problem: Deformation monitoring of high rockfill dams is essential for assessing their stability and preventing potential failures and landslides.
Key Innovation: Development of an advanced data reliability assessment method specifically tailored for high rockfill dam deformation analysis.
71. Assessing the probabilistic evolution of cascading hazards of landslide-river blockage-dam breaching-flood by integrating physics-based and data-driven methods
Core Problem: Cascading hazards involving landslides, river blockages, dam breaching, and floods pose significant risks to downstream communities and infrastructure.
Key Innovation: Integration of physics-based and data-driven methods to assess the probabilistic evolution of these cascading hazards.
72. An extended vector inclination method for inferring detailed slip surfaces beneath landslides from SAR and optical satellite remote sensing image
Core Problem: Inferring detailed landslide slip surfaces is challenging.
Key Innovation: Extended vector inclination method using SAR and optical imagery.
73. Sentinel-1 imagery for wide-scale quantitative landslide vulnerability assessment of buildings
Core Problem: Assessing landslide vulnerability of buildings over wide areas.
Key Innovation: Using Sentinel-1 imagery for quantitative vulnerability assessment.
74. Mapping wide-area land subsidence from groundwater use in the North China plain by machine learning-based InSAR adjustment
Core Problem: Mapping land subsidence due to groundwater extraction.
Key Innovation: Machine learning-based InSAR adjustment for subsidence mapping.
75. Multi-source assessment of permafrost deformation along the Bei'an–Hei'he highway in Northeast China
Core Problem: Assessing permafrost deformation impacts on infrastructure.
Key Innovation: Multi-source remote sensing for permafrost deformation monitoring.
76. Groundwater volume loss and land subsidence in the North China plain investigated using wide-area InSAR surveying and mechanical modeling
Core Problem: Investigating land subsidence due to groundwater loss.
Key Innovation: InSAR surveying and mechanical modeling for subsidence analysis.
77. Nationwide mapping and characterization of land subsidence in the United States using InSAR
Core Problem: Mapping and characterizing land subsidence across the US.
Key Innovation: InSAR-based nationwide land subsidence mapping.
78. An enhanced spatiotemporal prediction method on landslide displacement with LDP-ConvFormer and MT-InSAR observations
Core Problem: Predicting landslide displacement accurately in space and time.
Key Innovation: LDP-ConvFormer model with MT-InSAR for landslide displacement prediction.
79. Phase gradient rate constrained minimum cost flow: A robust unwrapping method for landslides with large deformation gradients
Core Problem: Unwrapping InSAR data for landslides with large deformation gradients.
Key Innovation: Phase gradient rate constraint in minimum cost flow method.
80. Satellite-derived seasonal fluctuations in surface displacement and soil moisture: Implications for landslide activity
Core Problem: Understanding the relationship between seasonal surface displacement, soil moisture, and landslide activity.
Key Innovation: Using satellite remote sensing to monitor surface displacement and soil moisture fluctuations to assess landslide activity.
81. Debris covered glacier mapping using newly annotated multisource remote sensing data and geo-foundational model
Core Problem: Mapping debris-covered glaciers using remote sensing data.
Key Innovation: Using multi-source remote sensing data and a geo-foundational model to map debris-covered glaciers.
82. Advances in mitigating InSAR non-closure phase bias: A refined processing approach
Core Problem: Mitigating InSAR non-closure phase bias for improved ground deformation monitoring.
Key Innovation: A refined InSAR processing approach to reduce phase bias and improve deformation measurement accuracy.
83. Investigating seasonal velocity variations of selected glaciers in high mountain asia
Core Problem: Monitoring glacier velocity variations in High Mountain Asia.
Key Innovation: Using remote sensing data to investigate seasonal glacier velocity changes.
84. Synergistic effects of drip irrigation and vegetation on the stability of biochar-stabilized expansive soil slopes
Core Problem: Expansive soil slopes are prone to instability, requiring effective stabilization methods.
Key Innovation: Drip irrigation and vegetation combined with biochar to enhance slope stability in expansive soils.
85. Effects of gully topographic vertical zone on the spatial heterogeneity of root-soil complex shear performance in the loess plateau
Core Problem: Gully erosion in the Loess Plateau leads to soil loss and land degradation.
Key Innovation: Investigating the impact of gully topography on root-soil shear performance to understand erosion processes.
86. Wave erosion induced bank collapse and its impact on landslides: insights from model tests
Core Problem: Wave erosion causes bank collapse, triggering landslides and coastal instability.
Key Innovation: Model tests to understand the relationship between wave erosion, bank collapse, and landslide initiation.
87. Landslide susceptibility zoning through physically-based limit equilibrium method modelling
Core Problem: Landslide hazard assessment requires accurate susceptibility zoning.
Key Innovation: Using physically-based limit equilibrium methods for landslide susceptibility zoning.
88. Multi-disciplinary reconstruction of debris flow events and dynamics in the Northern Apennines, Italy: A multi-scale approach linking ground evidence with climatic triggers
Core Problem: Debris flows pose a significant hazard in mountainous regions.
Key Innovation: Multi-disciplinary approach to reconstruct debris flow events and link them to climatic triggers.
89. Prediction of aspect-dependent soil thickness and its influence on landslide susceptibility
Core Problem: Landslide susceptibility is influenced by soil thickness, which varies with slope aspect.
Key Innovation: Predicting soil thickness based on aspect and assessing its impact on landslide susceptibility.
90. Automated gully erosion extraction in the typical black soil region of Northeast China using a deep learning approach based on multi-source remote sensing data
Core Problem: Gully erosion in black soil regions leads to significant land degradation.
Key Innovation: Using deep learning and multi-source remote sensing data for automated gully erosion extraction.
91. Mechanistic analysis of root morphology on shear behavior in root-soil composites using discrete element method (DEM)
Core Problem: Root reinforcement is crucial for slope stability, but the mechanisms are complex.
Key Innovation: Using DEM to analyze the influence of root morphology on the shear behavior of root-soil composites.
92. What drives gullies in Spain’s olive landscapes? A regional analysis of gully activity
Core Problem: Gully erosion is a major problem in olive landscapes, leading to soil loss and land degradation.
Key Innovation: Regional analysis to identify the driving factors of gully activity in olive landscapes.
93. Climate snow-avalanche linkage revealed by geomorphological, historical and tree-ring records in the central Spanish Pyrenees
Core Problem: Understanding the relationship between climate and snow avalanches is crucial for hazard management.
Key Innovation: Using geomorphological, historical, and tree-ring records to reveal the climate-snow avalanche linkage.
94. Temperature-dependent shear behavior of glacial till-ice composite: Experimental insights from the southeastern Tibetan Plateau
Core Problem: Understanding the shear behavior of glacial till-ice composites under varying temperatures.
Key Innovation: Experimental investigation of temperature's influence on glacial till-ice composite shear behavior.
95. Shear strength-temperature-moisture content relationship of warm frozen ground for thaw slump stability analysis
Core Problem: Analyzing the stability of thaw slumps in warm frozen ground.
Key Innovation: Examining the relationship between shear strength, temperature, and moisture content in warm frozen ground to assess thaw slump stability.
96. Failure mechanism and stability control of fault induced by underground cavern excavation: insights from theoretical analysis and numerical modeling
Core Problem: Understanding the failure mechanisms of faults induced by underground cavern excavation.
Key Innovation: Using theoretical analysis and numerical modeling to investigate fault failure and stability control during underground excavation.
97. Mechanical performance evaluation of buried pipelines with corrugated flexible joints under fault displacements
Core Problem: Assessing the mechanical performance of buried pipelines with flexible joints under fault displacement.
Key Innovation: Evaluating the performance of buried pipelines with corrugated flexible joints subjected to fault movements.
98. Dynamic response of density-graded ice-rich frozen soil under impact loading in frozen shafts: an experimental, theoretical, and numerical study
Core Problem: Analyzing the dynamic response of ice-rich frozen soil under impact loading.
Key Innovation: Combining experimental, theoretical, and numerical methods to study the dynamic behavior of density-graded ice-rich frozen soil in frozen shafts.
99. Deformation characteristics and progressive failure mechanism of layered carbonaceous slate tunnel based on a discrete–continuum coupling method
Core Problem: Investigating the deformation and failure mechanisms of layered carbonaceous slate tunnels.
Key Innovation: Using a discrete-continuum coupling method to analyze the deformation characteristics and progressive failure of layered carbonaceous slate tunnels.
100. SBAS-InSAR analysis for ground settlement in longest railway tunnel in South Korea
Core Problem: Monitoring ground settlement in a railway tunnel.
Key Innovation: Using SBAS-InSAR to analyze ground settlement in a long railway tunnel.
101. Thawing permafrost under Qinghai-Xizang Highway and its impacts on road performance based on multi-source observed data
Core Problem: Assessing the impact of thawing permafrost on road performance.
Key Innovation: Using multi-source observed data to evaluate the effects of thawing permafrost on the Qinghai-Xizang Highway.
102. Shear strength-temperature-moisture content relationship of warm frozen ground for thaw slump stability analysis
Core Problem: Analyzing the stability of thaw slumps in warm frozen ground.
Key Innovation: Examining the relationship between shear strength, temperature, and moisture content in warm frozen ground to assess thaw slump stability.
103. Stress redistribution of loess due to tunnelling of shallow tunnels
Core Problem: Understanding stress redistribution in loess due to tunneling.
Key Innovation: Analyzing stress redistribution in loess soils caused by shallow tunnel construction.
104. Dynamic response of an underground structure subjected to internal erosion and seismic densification via centrifuge shaking table tests
Core Problem: Analyzing the dynamic response of underground structures to internal erosion and seismic densification.
Key Innovation: Using centrifuge shaking table tests to study the dynamic behavior of underground structures subjected to internal erosion and seismic densification.
105. Predicting rockfall hazard with deep learning: Latent feature extraction from geological layers
Core Problem: Rockfall hazard prediction is challenging due to complex geological factors.
Key Innovation: Deep learning to extract latent features from geological layers for improved rockfall hazard prediction.
106. Fragmentation and energy dissipation in rockfall: Effects of block shape and non-collinear impact dynamics
Core Problem: Understanding rockfall fragmentation and energy dissipation is crucial for hazard assessment.
Key Innovation: Investigating the effects of block shape and non-collinear impact dynamics on rockfall fragmentation and energy dissipation.
107. Multi-task deep transfer learning for complicated seismic dynamic response prediction in slope systems
Core Problem: Predicting seismic dynamic response in slope systems is complex and requires advanced modeling techniques.
Key Innovation: Using multi-task deep transfer learning to improve the prediction of seismic dynamic response in slope systems.
108. Topographic and morphological effects of global earthquake- and rainstorm-induced landslides
Core Problem: Landslides induced by earthquakes and rainstorms pose significant hazards globally.
Key Innovation: Analyzing the topographic and morphological effects on earthquake- and rainstorm-induced landslides on a global scale.
109. Harnessing LoRa for real-time landslide monitoring and early alerts in Kerala’s terrain
Core Problem: Real-time landslide monitoring and early warning systems are essential for mitigating landslide risks.
Key Innovation: Implementing a LoRa-based system for real-time landslide monitoring and early alerts in the challenging terrain of Kerala.
110. Cross-regional extrapolation of landslide susceptibility mapping via transfer learning
Core Problem: Landslide susceptibility mapping is often limited by data availability and transferability across regions.
Key Innovation: Using transfer learning to extrapolate landslide susceptibility maps across different regions, improving prediction accuracy in data-scarce areas.
111. Landslide susceptibility assessment using machine learning with a novel SHAP-based sampling strategy
Core Problem: Accurate landslide susceptibility assessment is crucial for effective hazard management.
Key Innovation: Integrating a novel SHAP-based sampling strategy with machine learning to enhance landslide susceptibility assessment.
112. A catchment-scale landslide hydro-mechanical coupling model considering spatial heterogeneity
Core Problem: Landslide modeling at the catchment scale requires considering the hydro-mechanical coupling and spatial heterogeneity.
Key Innovation: Development of a catchment-scale hydro-mechanical coupling model for landslide analysis, incorporating spatial heterogeneity.
113. From preferential infiltration pathways to their modes of occurrence: preferential flow-induced soil strength attenuation regulates shallow loess landslide behavior
Core Problem: Shallow loess landslides are influenced by preferential infiltration pathways and soil strength attenuation.
Key Innovation: Linking preferential infiltration pathways to soil strength attenuation in shallow loess landslides.
114. Rapid flood inundation mapping for dam failure and operations
Core Problem: Rapid flood inundation mapping is crucial for dam failure scenarios and operations.
Key Innovation: Developing methods for rapid flood inundation mapping in the context of dam failure and operations.
115. Beyond depth-direction segregation: Independent flow-direction mechanisms drive size segregation in granular flows
Core Problem: Understanding size segregation in granular flows.
Key Innovation: Identifying independent flow-direction mechanisms that drive size segregation in granular flows.
116. A GSA-ML hybrid framework combined key geological parameters selection for deformation prediction of fractured rock slopes
Core Problem: Deformation prediction of fractured rock slopes.
Key Innovation: Hybrid GSA-ML framework for geological parameter selection.
117. Adaptive FEM-SPH for anchored slope failure with fractal dimension crack analysis
Core Problem: Analysis of anchored slope failure.
Key Innovation: Adaptive FEM-SPH coupling with fractal dimension crack analysis.
118. Development of a constitutive model for unsaturated vegetated soils and its application for rainfall-induced deformations of vegetated slopes
Core Problem: Rainfall-induced deformations of vegetated slopes.
Key Innovation: Constitutive model for unsaturated vegetated soils.
119. Reliability analysis of landslide stabilization with pile groups considering spatial variability of soil properties
Core Problem: Landslide stabilization with pile groups.
Key Innovation: Reliability analysis considering spatial variability of soil.
120. A novel physics–data hybrid approach for slope stability assessment considering future rainfall patterns
Core Problem: Slope stability assessment.
Key Innovation: Physics-data hybrid approach considering future rainfall.
121. Seismic risk assessment of railway embankments on spatially variable loose deposit slopes: A stacking ensemble machine learning-based approach
Core Problem: Seismic risk assessment of railway embankments.
Key Innovation: Stacking ensemble ML for spatially variable slopes.
122. A SPH-DEM coupling method based on mixture theory for landslide-generated waves
Core Problem: Landslide-generated waves.
Key Innovation: SPH-DEM coupling based on mixture theory.
123. An integral extremum-based limit equilibrium method for stability analysis of frozen soil slopes considering random temperature fields
Core Problem: Stability analysis of frozen soil slopes.
Key Innovation: Limit equilibrium method considering random temperature fields.
124. Integrated early warning method for landslide acceleration and expansion based on GB‐InSAR monitoring
Core Problem: Landslide early warning.
Key Innovation: Integration of GB-InSAR monitoring for acceleration and expansion.
125. A Eulerian multiphase model for collapse and segregation of bidisperse granular columns
Core Problem: Collapse of granular columns
Key Innovation: Eulerian multiphase model for bidisperse granular columns
126. Transition From Fracture Propagation to Coalescence in Westerly Granite During the Preparation Process of Macroscopic Failure
Core Problem: Understanding the fracturing process in rock leading to macroscopic failure.
Key Innovation: Analyzing the transition from fracture propagation to coalescence in Westerly Granite during failure preparation.
127. Brief communication: Threshold and probability. The conceptual difference between ID thresholds for landslide initiation and IDF curves
Core Problem: Addressing the overlooked conceptual difference between intensity-duration thresholds and intensity-duration-frequency curves in landslide studies.
Key Innovation: Highlighting the distinction between duration in intensity-duration thresholds and intensity-duration-frequency curves for landslide initiation.
128. Assessing the predictive capability of several machine learning algorithms to forecast snow avalanches using numerical weather prediction model in eastern Canada
Core Problem: Improving snow avalanche forecasting using machine learning algorithms and numerical weather prediction data.
Key Innovation: Applying and comparing different machine learning methods for snow avalanche forecasting, demonstrating their potential to enhance hazard anticipation.
129. Identification of rainfall thresholds for debris-flow occurrence through field monitoring data
Core Problem: Defining rainfall thresholds for debris flows in data-scarce Alpine catchments for early warning systems.
Key Innovation: Developing a new method to define rainfall thresholds for debris flows based on field monitoring data, suitable for early warning in areas with limited data.
130. Use of delayed ERA5-Land soil moisture products for improving landslide early warning
Core Problem: Investigating the utility of delayed ERA5-Land soil moisture data for improving landslide early warning systems.
Key Innovation: Demonstrating that even with a 5-15 day delay, ERA5-Land soil moisture data can enhance the performance of landslide triggering models using artificial neural networks.
131. Deep learning-based object detection on LiDAR-derived hillshade images: insights into grain size distribution and longitudinal sorting of debris flows
Core Problem: Improving the analysis and monitoring of debris flows using LiDAR and deep learning techniques.
Key Innovation: Developing a method using laserscanners and deep learning to detect and track moving objects during debris flow events, enabling fast and accurate measurement of object speed and size.
132. Controls over debris flow initiation in glacio-volcanic environments in the Southern Andes
Core Problem: Understanding the factors controlling debris flow initiation in glacio-volcanic environments.
Key Innovation: Identifying that saturated volcanic soils above less permeable glacial deposits create ideal conditions for slope failures and debris flows in the Southern Andes.
133. Using network science to evaluate landslide hazards on Big Sur Coast, California, USA
Core Problem: Landslide events triggered by heavy rain cause instability and downhill movement of soil, rock, and debris.
Key Innovation: A statistical metric to track changing conditions in landslide-prone regions, aiding in early warning systems.
134. Mapping forest-covered landslides using Geographic Object-Based Image Analysis (GEOBIA), Jena region, Germany
Core Problem: Mapping landslides is essential for understanding hazards and risk assessment, but forest cover makes it difficult.
Key Innovation: Using a geographic object-based image analysis (GEOBIA) approach with high-resolution lidar data to map forest-covered historical landslides.
135. Sentinel-1 SAR-based globally distributed co-seismic landslide detection by deep neural networks
Core Problem: Rapid and accurate landslide detection is crucial for disaster response, but optical satellite imagery is limited by weather and illumination conditions.
Key Innovation: A framework for landslide rapid detection using radar and deep learning, trained and tested on data from diverse regions, offering high accuracy and rapid response potential.
136. A hybrid deep learning approach for highway landslide susceptibility assessment based on InSAR data
Core Problem: Assessing landslide susceptibility along highways using traditional methods can be time-consuming and less accurate.
Key Innovation: Using a hybrid deep learning approach with InSAR data to improve the efficiency and accuracy of highway landslide susceptibility assessment.
137. A KG-driven framework for enhanced post-failure landslide stability assessment
Core Problem: Post-failure landslide stability assessment is crucial for risk management, but current methods may lack comprehensive data integration.
Key Innovation: Developing a knowledge graph (KG)-driven framework to enhance post-failure landslide stability assessment by integrating diverse data sources.
138. Efficient multi-source deep learning for rapid landslide mapping in the Karst mountains of Bijie, China
Core Problem: Rapid and accurate landslide mapping in complex terrains like the Karst mountains is challenging using traditional methods.
Key Innovation: Employing efficient multi-source deep learning techniques for rapid landslide mapping, leveraging diverse data sources to improve accuracy.
139. Exploring the effect of soil zoning in the TRIGRS and Scoops3D integrated model on the stability of rainfall-induced shallow landslides
Core Problem: Accurately modeling the stability of rainfall-induced shallow landslides requires considering the spatial variability of soil properties.
Key Innovation: Integrating soil zoning into the TRIGRS and Scoops3D models to explore its effect on the stability assessment of rainfall-induced shallow landslides.
140. Landslide susceptibility assessment under future seismic and precipitation scenarios: a case study of the 2014 Mw 6.2 Ludian earthquake zone, Yunnan, China
Core Problem: Assessing future landslide susceptibility in areas affected by earthquakes and changing precipitation patterns is crucial for disaster preparedness.
Key Innovation: Evaluating landslide susceptibility under future seismic and precipitation scenarios, providing insights for risk management in earthquake-prone regions.
141. Rainfall-induced instability of mountainous photovoltaic slopes under spatially non-uniform infiltration
Core Problem: Rainfall-induced slope failures are frequent in mountainous regions, and photovoltaic (PV) installations exacerbate this due to non-uniform rainfall infiltration.
Key Innovation: Developing a coupled hydro-mechanical modeling framework to investigate slope instability under spatially heterogeneous rainfall caused by PV panel shading and runoff concentration.
142. Experimental study on the formation mechanism of landslides considering the spatial distribution of the locking section
Core Problem: Understanding the evolution processes of locked-segment landslides is challenging, leading to economic losses and casualties.
Key Innovation: Using model tests to analyze the evolution process, deformation patterns, and stress distribution of locked-segment landslides, proposing identification criteria for the evolution state.
143. Submarine landslides and canyons: slope degradation and shelf-edge indentation in a tectonically active margin (Finale Basin, Northern Sicilian Margin, Tyrrhenian Sea)
Core Problem: Submarine canyons and landslides are closely related geological features of continental margins, and their linkage varies depending on their geological and geodynamic setting.
Key Innovation: Analyzing multibeam bathymetric data and seismic lines to study continental margin degradation through canyon and landslide formation due to continental margin uplift and tilting.